Methods

Results

The highest peak ventilation among men (141.9±24.5 L·min−1) and women (92.0±16.5 L·min−1) was observed in the youngest age group (20–29 years, sex differences p<0.001) with an average 7% reduction per decade. The highest tidal volumes were observed in the 30–39 and 40–49 year age groups among men (2.94±0.46 L) and women (2.06±0.32 L) (sex differences p<0.001), with a subsequent average 6% reduction per decade. Ventilatory threshold and respiratory compensation point were observed at approximately 77% and 87% of peak oxygen uptake (VO2peak) among men and women, respectively. The best ventilatory efficiency (EqVCO2Than) was observed in the youngest age group (20–29 years) in both men (26.2±2.8) and woman (27.5±2.7) (sex differences p<0.001) with an average 3% deterioration in ventilatory efficiency per decade.

Conclusion

This is the largest European reference material of cardio-respiratory variables in healthy men and women aged 20–90 years, establishing normal values for, and associations between key cardio-respiratory parameters. This will be useful in clinical decision making when evaluating cardiopulmonary health in similar populations.

Funding: This study was funded by K.G. Jebsen Foundation, The Norwegian Council on Cardiovascular Disease, The Research Council of Norway, Foundation for Cardiovascular Research at St. Olav's Hospital, Norwegian State Railways, Roche Norway Incorporated and Valnesfjord Rehabilitation Center. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: This study was funded in part by Roche Norway Incorporated Center. There are no disclosures to report or any conflicts of interest. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Introduction

Cardiopulmonary exercise testing (CPET) is an underutilized clinical procedure [1], despite several published recommendations by international health organizations [2]–[5]. It is a good tool for evaluating mechanisms and limitations of exercise tolerance [6], and for the assessment of cardiopulmonary health [1]. Consequently, CPET is a valuable tool in clinical decision making [2]. There are numerous large studies establishing spirometry reference values [7]–[14]. However, studies containing a combination of principal cardio- respiratory variables, such as ventilation (VE), tidal volume (VT), breathing frequency (fB), oxygen uptake (VO2), expired carbon dioxide (VCO2) and ventilatory efficiency (EqVCO2) are limited. Previous research have included only a few of these key variables, are limited to selected age groups and fitness levels, or small populations e.g. [15]–[25]. The aim of this study was to establish a large reference material on submaximal and maximal cardiopulmonary variables in healthy men and women aged 20–90 years.

Methods

Participants

The HUNT 3 fitness study is the third wave of the Nord-Trøndelag Health Studies (ntnu.edu/hunt). Data were collected between October 2006 and June 2008. The entire population >20 years of age (n = 94194) were invited to participate, 54% (n = 50821) accepted. Eligible candidates had to be free from cardiovascular disease, respiratory symptoms, cancer, and the use of blood pressure medication. Based upon self-reported information, 30513 candidates presented as suitable for VO2max testing. Out of these, 12609 candidates resided in the 3 municipals selected for VO2max testing, and 5633 of them volunteered to participate. Subsequent the primary inclusion the medical interview excluded an additional 390 candidates not meeting medical inclusion criteria, leaving 5243 candidates. 4631candidates completed a VO2peak test. These 3 locations were chosen due to geographical location to minimize travel distance for participants. We experienced technical difficulties with Cortex MetaMax ∏, and during service at Cortex data was lost, thus, total sample sizes on tidal volume (VT) and breathing frequency (fB) was n = 3667.

Ethics statement

The study was approved by the Regional committee for medical research ethics (2012/1672/REK nord), the Norwegian Data Inspectorate and the National Directorate of Health, and is in compliance with the Helsinki declaration. Written informed consent was obtained from all participants.

Cardio Pulmonary Exercise Test (CPET)

An individualized graded protocol [26] was used for measuring cardio-respiratory variables (Cortex MetaMax ∏, Cortex, Leipzig, Germany). Before starting the testing procedure several MetaMax II apparatus were tested against Douglas-bag and iron lung (Cortex, Leipzig, Germany) and those finally used found reliable and valid [27]. Speed and angle of the test treadmills were calibrated prior to testing. The MetaMax II was calibrated prior to the first test each day using a standard two-point gas calibration procedure. The calibration included measurements of ambient air and a gas mix of known content (15.03% O2 and 4.98% CO2 in N2), a calibration of the Triple-V volume transducer with a calibrated 3 L syringe (Calibration syringe D, SensorMedics, CareFusion, San Diego, CA, USA), and barometric pressure control. Volume calibration was performed every third test and the two-point gas calibration every fifth. Before each test the ambient room air was checked. Heart rate was measured by radio telemetry (Polar S610i, Polar Electro Oy, Kempele, Finland). Body mass was measured using the weighing scale Model DS-102 (Arctic Heating AS, Nøtterøy, Norway). Participants had a treadmill familiarization phase of 8–10 minutes during warm-up. They were instructed to avoid grabbing the handrails if not absolutely necessary. The individualized warm-up workload determined the initial speed/angle on the subsequent treadmill test. Candidates used a face mask (Hans Rudolph, Germany) of appropriate size linked to the MetaMax ∏. When participant maintained a stable oxygen uptake >30seconds, velocity (0.5–1.0 kmh-1) or inclination (1–2%) was increased. Increased workload was if possible obtained with increased speed and keeping a fixed slope angle of the treadmill. If a participant was unable to increase speed, the angle was increased. Tests were ended when candidates reached volitional exhaustion (e.g. shortness of breath and leg fatigue). VO2max was considered achieved if subjects reached a VO2 plateau that remained stable even with increased work load [28], i.e. VO2 did not increase more than 2 mL·kg−1·min−1 despite increased work load, and R≥1.05. Since 12.6% of the subjects failed to reach VO2max we used the expression VO2peak. Measurements were done at 3 different workloads, 2 submaximal and peak. Level 1: The individual initial workload was determined during warm-up, and stable VO2 and heart rate were reached after 3 minutes. Level 2: Treadmill gradient was increased by 2% or speed increased 1 km•h−1, with steady state obtained after 2–3 minutes. Peak workload is described above.

The transition point from aerobic to anaerobic metabolism denotes VThan[29]. With increasing workload aerobic metabolism alone cannot provide the energy required, and energy production must increasingly depend upon anaerobic metabolism [30]. RCP marks the respiratory compensation for metabolic acidosis, beneath which VE is strongly linked to VCO2, whereas above VE increases faster relative to VCO2[31], hence, onset of hyperventilation [32]. Both VTHan and RCP were established by the V-slope method [31].

Ventilatory efficiency

We calculated the ventilatory equivalent EqVO2 (VE·VO2−1) and EqVCO2 (VE·VCO2−1) at VO2peak and VThan. The ventilatory equivalents describe the fraction of minute ventilation (VE) to oxygen uptake (VO2), or to expired carbon dioxide (VCO2).

Statistical analysis

Parametric analysis was used and QQ-plots supported the assumption of normally distributed data. Data are presented as arithmetic mean ± standard deviation. Analysis of variance (Anova) was used to determine differences between age groups. If a significant F-ratio was achieved, post hoc evaluations were completed using Bonferroni tests. An Independent-Samples T-test was used for establishing level of significance between sexes. Linear regression and curve linear regression, with 95% confidence interval, were used to test associations between cardio-respiratory parameters. Multiple linear regressions were used to generate prediction models. All statistical tests were two-sided. SPSS 20.0 (Statistical package for Social Sciences, Chicago; Illinois, USA), and GraphPad Prism 4.01 (GraphPad Software, San Diego, California, USA) were used to analyze data. Correlations were done using data from Level 1, Level 2 and peak as described above. A p-value of <0.05 was considered statistically significant.

Results

Descriptive characteristics for men and women are presented in Table 1.

Peak ventilation (VEpeak) and tidal volume (VTpeak)

Women had a 34% (p<0.001) lower VEpeak than men. VEpeak was similar and highest in the two youngest age groups (20–29 and 30–39 years) in both men and women. In women VEpeak became 8% (p<0.01) lower per decade from age 30–39 up to 60–69 years. Compared to men aged 20–39 years, men aged 40–49 years had 3.5% (p<0.05) lower VEpeak, whereupon it decreased by 9% (p<0.001) per decade up to those aged 60–69 years. For both sexes we observed an average 16% (p<0.001) lower VEpeak between the 2 most senior age groups (60–69 vs. +70 years) (Table 2).

Women had approximately 32% (p<0.001) lower VTpeak than men. For both sexes the highest VTpeak was found among those aged 30–49 years, despite no differences in stature compared to the youngest age groups. In both sexes we observed an average 4% (p<0.05) and 11% (p<0.001) drop in VTpeak per decade in age groups 40–69 years, and between the 2 most senior age groups, respectively (Table 2). The highest breathing frequency (fB) in both men and women, 50±9 breaths·min−1 and 47±7 breaths·min−1, respectively, was found in the youngest age group (20–29 years), with an average 5% (p<0.05) decrease per subsequent decade (Table 2).

Stratified by height an 11% (p<0.01) rise in VEpeak and VTpeak was observed per 10 cm increased height, in both sexes (Table 3).

Carbon dioxide (VCO2) elimination

Women displayed roughly 34% (p<0.001) lower VCO2peak than men. Stratified by age the highest VCO2peak was found in the youngest age groups. No significant differences in VCO2peak were observed neither for men nor women between age groups 20–29 and 30–39 years, whereupon an approximate 6% (p<0.001) and 5% (p<0.001) decrease was observed between age groups 30–39 vs. 40–49 years, respectively. In subsequent age groups exponential reductions were observed, ending with an average 18% (p<0.001) lower peak VCO2 in the most senior age group compared with men and women aged 60–69 years (Table 2).

Ventilatory anaerobic threshold (VThan)

The highest VThan was observed in the youngest age groups. No statistical differences in VThan was observed between the 3 youngest age groups (20–49 years) among both sexes, whereupon we observed an approximate 10% (p<0.001) lower VThan per decade. VThan was obtained at 75.2±10.7 and 76.7±9.4% of VO2peak for men and women (20–29 years), respectively, which corresponds to approximately 88±7% of peak heart rate (fcpeak), with no major differences between age groups (Table 4).

Respiratory compensation point (RCP)

The highest RCP was observed in the youngest age groups with roughly the same decline rate per decade as observed for VThan (Table 4).

Ventilatory efficiency at VO2peak and at VThan

EqVO2peak were similar between sexes and age groups. EqVCO2peak was on average 1.2% (p<0.05) higher in women than in men. In men aged 20–59 years no differences were observed between subsequent age groups, upon which we observed a 4.4% (p<0.001) higher EqVCO2peak for men aged 60–69 years compared to those aged 50–59 years. No differences were shown between the two oldest male age groups. In women we observed no differences in EqVCO2peak between subsequent age groups throughout all decades. Comparing the youngest and oldest age groups an 8% (p<0.001) higher EqVCO2peak was observed in the oldest age group, in both men and women (Table 5).

EqVO2Than was on average 3% (p<0.001) higher in women than in men. EqVO2Than was similar and lowest in the two youngest male age groups (20–29 and 30–39 years). We observed a 5.2% (p<0.05) higher EqVO2Than for men aged 40–49 years compared to those aged 30–39 years, with no differences between the subsequently older male age groups (40–49 through +70 years). In women no differences were observed between subsequent age groups throughout all decades. When comparing the youngest and oldest age groups a 12% (p<0.05) higher EqVO2Than was observed in the oldest age group, among both men and women (Table 5).

EqVCO2Than was on average 2.5% (p<0.001) higher in women compared to men. EqVCO2Than was alike and lowest in the two youngest male age groups (20–29 and 30–39 years), whereas a 4.9% (p<0.01) higher EqVCO2Than was observed in men 40–49 years compared to the 30–39 years group. No differences were found between men aged 40–49 years and 50–59 years, whereupon an average 5.3% (p<0.05) higher EqVCO2Than was observed per decade between the three oldest male age groups. In women aged 20–69 years no differences in EqVCO2Than was observed between subsequent age groups, upon which a 5.4% (p<0.05) higher EqVCO2Than was observed in the oldest age group compared to those 60–69 years. Comparing the youngest and the oldest age groups showed a 16% (p<0.001) higher EqVCO2Than in the oldest group, in both men and women (Table 5).

EqVCO2VThan, among the 3 oldest age groups, stratified by fitness quartiles

In those aged 50–59 years there was a 7.2% (p<0.05) and 8.2% (p<0.001) increase between the most fit (Q1) and least fit (Q4), men and women, respectively. The middle (60–69 years) and the most senior groups (+70 years) had increases of 13.4% (p<0.001; men) vs. 13.1% (p<0.001; women), and 16.4% (p<0.01; men) with no significant differences among women, between the fittest (Q1) and least fit (Q4), respectively (Table 6).

Prediction equations for VEpeak, VCO2peak and VThan were derived from non-exercise variables, including weight, height, age and sex. Weight and age proved negligible in predicting VTpeak, as did weight and height in predicting EqVCO2VThan and EqVO2VThan, hence these variables were excluded from the respective models. For all models gender should be substituted with 1 or 2 for men and women, respectively. The final regression models are presented in table 7. Non-exercise prediction models for VO2peak are previously published from the HUNT 3 fitness material [33].

Discussion

This is the largest European cardio-respiratory reference material in healthy men and women aged 20–90 years. Previous papers mostly present smaller, selected age groups [15], [18], [34]–[40], or only male populations [23], [25], [41]. Hence, this study will serve as a useful addition to previous research.

Sex and age group differences in peak ventilation (VEpeak) and tidal volume (VTpeak)

In this study women had approximately 34% and 32% lower VEpeak and VTpeak, respectively, and a 4% lower peak fBpeak than men. This is in agreement with other population-based studies on VEpeak[39], [42]–[44], VTpeak and fBpeak[22], [45], and as expected as women have smaller lung size and dynamic lung function volumes than men, also after adjusting for differences in stature [46]. We observed 6–30% higher VEpeak among men and women compared to that seen in Brazilian [42] (n = 3992), American [43] (n = 988) and French [44] (n = 150) populations, as well as in small sample size studies [22], [45], [47], [48]. Yet, a Norwegian study [49] (n = 759) displays VEpeaks fairly consistent with ours. Hence, there might be population differences, which highlight the need of reference data in different populations.

In this study the highest VTpeak was observed among the 30–49 year groups, in both men and women, with a decrease in subsequent age groups. These findings are unexpected, since the highest VT should be in the youngest age group, with deterioration between subsequently older age groups [50], [51]. Our findings could be explained by the relative low sample size in the youngest age group. Contrary to us a Canadian [39] (n = 100) and Israeli [23] (n = 1424) study presented their highest VTpeak in the youngest age groups (15–25 yrs). Interestingly, while the Canadian study displayed the same male average VTpeak as us, they have significantly lower VEpeak, signaling a necessarily lower fBpeak (not displayed).

Association between VT and VE below and above VThan

On the initial sub maximal workloads the VT vs. VE slope displays a steeper gradient than towards test termination. This is to be expected, since it is well established that VT increases steeper than fB below VThan, whereas fB mostly accounts for the increase in VE at workloads above VThan[47], [52].

Sex and age group differences in VThan and RCP

We observed VThan at an average 77% of VO2peak, in both sexes, and in line with other studies (n = 204–3992) [24], [40], [42], [53], [54] minor sex differences. Previous studies report VThan at significantly lower fractions (49–70% of VO2peak) [23], [24], [40], [42], [53], [54], or more consistent to that observed by us [25], [55], [56]. Differences are most likely caused by use of different methods and analyzing approaches applied in the different studies, which makes direct comparisons difficult [23], [25], [42], [55], [56].

In this study VThan was observed at ≈75% in the youngest age groups and at ≈80% of VO2peak in the oldest age groups, in both men and women, with significant differences (p<0.05) between the youngest and the 60–69 year age group. Age related increase in VThan (as percent of VO2peak) is reported in previous studies as well [23]–[25], [42], [44], [53], [54], [57]. This is to be expected since VThan (L·min−1) declines at a slower rate than VO2peak (L·min−1) with increasing age [58], [59], and consequently occurs at a higher percent of VO2max/peak[60]. This is suggested to be, at least partly, due to changes in skeletal muscle composition associated with increasing age, with the selective loss of type ΙΙ fibers and therefore a relative increase in type Ι fibers [61]. Contrary to this Lenti and colleagues [34] report a decrease in percent VThan in a trained senior group (n = 16), compared to their young trained, whereas the untrained groups are consistent with our findings (n = 16). The small sample size taken into account, their data must be interpreted with caution.

RCP was observed at 86% and 90% of VO2peak, among men and women, respectively. This is consistent with the findings of several other studies [18], [35], [37]. However, direct comparisons are difficult due to their small sample sizes (n = 9–22) and the use of different measuring methods.

Ventilatory efficiency stratified by sex

In line with previous studies [17], [22] we observed similar EqVO2peak in men and women. Wasserman [52] suggests that EqVCO2 should be determined at VThan, or between VThan and RCP as VE is least variable in this range. Our submaximal level 2 measurements are close to VThan and we observed slightly higher (p<0.001) EqVCO2VThan in women than men, hence indicating less efficient ventilation in women. These observations are in agreement with previous studies [19], [20], [62]. Women's lower ventilatory efficiency might be explained by differences in ventilatory stimuli (e.g. [H+], [K+]), metaboreceptors, and central command [63], [64].

Ventilatory efficiency at VThan stratified by age groups

We observed deterioration in ventilatory efficiency, both in EqVO2Than (p<0.05) and EqVCO2Than (p<0.001), between the youngest and oldest age groups. This is in agreement with the findings of other studies (n = 69–474) [19], [20], [57], [62]. It is presently uncertain which factors are responsible for diminished ventilatory efficiency during exercise with increasing age [65]. Clearly, increased dead space might be a major contributing factor, as well as the lung's mechanical limitation to airflow, which deteriorate as the lung loses elastic recoil with increasing age [66]. In women evidence points to decreased leg muscle strength as a contributing factor [65]. Other suggestions are factors linked to muscle afferent excitability as a result of fiber type shifts [67], and neuromuscular alterations with growing age [68].

EqVCO2VThan stratified by fitness quartiles

Individuals in the three oldest age groups (50–59, 60–69, +70 years) in the present study are more likely to be referred to clinical exercise testing than younger age groups, and have been studied in more depth than other age groups when it comes to EqVCO2VThan. Interestingly, among individuals in these age groups approximately 25% had EqVCO2VThan higher than 30. EqVCO2VThan <30 is considered normal with a possible increase among older age groups [1]. In these age groups we observed minor differences in EqVCO2VThan between those that were among the three first quartiles of fitness (VO2peak quartiles), whereupon we observed a significant drop in ventilatory efficiency (hence, an increase in EqVCO2VThan) in those categorized as being least fit (Q4) in both sexes and all three age groups. All fitness quartiles in the oldest age group (+70 years), and the least fit quartiles in the two younger age groups (50–59, 60–69 years) had EqVCO2VThan ≈>30, which could be caused by high dead space ventilation due to diminished alveoli perfusion [19]. More importantly, diminished ventilatory efficiency can reflect disease severity and prognosis in several patient groups including chronic obstructive pulmonary disease, pulmonary arterial hypertension, hypertrophic cardiomyopathy and interstitial lung disease [1], [15], and are displayed in the range 41–60 in more severe cases of congestive heart failure [15]. Although we cannot totally exclude the possibility of unknown diseases in some of our participants, the self-report and medical interview, adhering to our inclusion criteria, provides a healthy population. Therefore seen in context of our sample size our findings may represent normal ventilatory efficiency values for the oldest age groups and least fit population.

Non-exercise prediction models for key cardio-respiratory variables

There is a plethora of VO2peak prediction models. However, models on other key cardio-respiratory variables are less abundant. The accuracy of previously published models on VO2peak from the HUNT 3 fitness data (Men: 12.8%, Women: 14.3%) [33] is in fair agreement with previous large sample studies (Jurca 2005). Smaller sample studies [69]–[71] with uniform populations [72], [73] show accuracies in the range ±7–17%. Also VThan accuracy (±19.9%) is approximately the same compared to 7 previous small-scale studies [40]. Our precision of VEpeak prediction (±17.2%) is in agreement with a large study of males [23], contrasted by a small study [39] showing 28% accuracy. However, it was hard to compare our VTpeak accuracy (±15.5%) with others [23], since key data was not presented. The 12.1% accuracy in predicting EqVCO2VThan was similar to a small sample study [62]. Our prediction models will provide a rough estimation of these key variables, regardless of gender and age. Moreover, the models use non-exercise variables that are easy to measure, thus making these models easy to use in both clinical settings and for recreational athletes.

Association between ventilatory efficiency and workload

The slope of the ventilatory equivalent for oxygen (EqVO2·W−1) increases with rising workload (w), which demonstrates reduced ventilatory efficiency as the workload increases. This is supported by two former case studies [30], [52]. More interestingly the EqVCO2·W−1 displays a gradient close to zero, which indicates a constant ventilatory efficiency throughout the incremental workload, and is in fair agreement with Wasserman and colleagues [52], yet, contradicted by another study [30] that presents an increase in EqVCO2 as the workload approaches peak. However, it is noteworthy that these studies are based on single case observations, and thus difficult to compare with our findings.

Strengths and limitations

The large sample size, inclusion of men and women, wide age distribution and cardio-respiratory measurements up to the true VO2max makes this study robust. The lack of spirometry data limits the assessment of ventilatory parameters. Also this study may be subject to bias due to self-selection caused by the low participation rate. However, almost all those invited to the current Fitness study from the large HUNT study agreed to participate in the fitness test. Due to limited capacity at the test sites resulting in long waiting lines, some potential participants chose to withdraw their participation from the study. Those who finally participated in the study could thus be healthier than those who quit or declined participation. However, a comparison of the participants in the fitness study with a healthy sample of the total HUNT population (i.e. free from cardiovascular or pulmonary diseases, cancer, or sarcoidosis) confirmed that the fitness participants did not considerably differ from other healthy HUNT participants [26].

Conclusions

The selection of key cardio-respiratory variables combined with an age and sex stratified large sample size makes this material unique. The inconsistencies between this and earlier research, and the scarce availability of large sample size materials support the usefulness of a large reference material as presented in this study. The HUNT 3 Fitness study presents the largest European reference material of cardio-respiratory variables in healthy men and women aged 20–90 years. Our material establishes normal values for, and associations between, as well as providing prediction models for these key cardio-respiratory parameters.

Acknowledgments

The HUNT 3 fitness study is a collaboration between The HUNT research center (Faculty of Medicine, Norwegian University of Science and Technology, NTNU), Nord-Trøndelag County Council and The Norwegian Institute of public Health, Liaison Committee between the Central Norway Regional Health Authority (RHA) and the Norwegian University of Science and Technology (NTNU).

Author Contributions

Conceived and designed the experiments: UW. Performed the experiments: UW. Analyzed the data: HL SS UW. Contributed reagents/materials/analysis tools: HL SS UW. Wrote the paper: HL SS UW. Contributed substantially to design, analysis and interpretation of data, final approval of manuscript and was accountable for all aspects of the work: HL SS UW. Drafted manuscript: HL. Critical revision of manuscript for important intellectual content: SS UW. Conception and acquisition of work: UW.

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Task Force of the Italian Working Group on Cardiac Rehabilitation Prevention Working Group on Cardiac R, Exercise Physiology of the European Society of Cardiology Piepoli MF, Corra U, et al. (2006) Statement on cardiopulmonary exercise testing in chronic heart failure due to left ventricular dysfunction: recommendations for performance and interpretation. Part I: definition of cardiopulmonary exercise testing parameters for appropriate use in chronic heart failure. Eur J Cardiovasc Prev Rehabil 13:150–164.